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Record W7115900083 · doi:10.5281/zenodo.17957842

The Doctrine of Separation of Powers: Functional Counterparts, British Fusion & Global Governance.

2025· preprint· en· W7115900083 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typepreprint
Languageen
FieldSocial Sciences
TopicEnvironmental law and policy
Canadian institutionsnot available
Fundersnot available
KeywordsSeparation of powersDoctrineAccountabilitySovereigntyCorporate governanceCivil libertiesParliamentary sovereigntyConstitutional law

Abstract

fetched live from OpenAlex

Description This work develops a contemporary doctrine of separation of powers reframed as a functional and resilience-based constitutional system. It argues that classical tripartite separation is insufficient to address modern systemic risks such as welfare failure, economic fragility, privatisation of essential services, environmental degradation, and global interdependence. The article introduces two constitutional counterparts within The Liberty System: the People’s counterpart, requiring enforceable guarantees of welfare, dignity, and civil liberties, and the Economic counterpart, requiring fiscal solvency, sustainability, and long-term economic stability. Rather than relying primarily on litigation, the framework emphasises institutional design, decentralised accountability through parish-level governance, and judicial review as a stabilising mechanism. Drawing on comparative constitutional models (including the UK, EU, South Africa, Canada, India, and the United States), the work addresses the risks of fused powers, privatisation, and executive dominance, and proposes buy-back sovereignty as a resilience option. The paper further situates separation of powers within a global governance context, outlining readiness for data-driven and quantum-enabled accountability while remaining grounded in civil liberties traditions rooted in the Magna Carta. The doctrine is presented as a scalable constitutional framework capable of operating across local, national, and global governance systems, integrating human, animal, and environmental protection with economic sustainability.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.022
Scholarly communication0.0060.006
Open science0.0010.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0060.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.296
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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